code: def read(self, model_path):
      with open(model_path, "rb") as f:
          for line in f:
              line = line.decode("utf-8")
  
              if "\\ x" in line or "xc3" in line:
                  continue
  
              fields = line.split("|||")
              constituents = fields[0].strip()[1:-1].split("/")
              phrase = fields[1].strip()
              paraphrase = fields[2].strip()
  
              # filter multiple words
              if len(phrase.split()) != len(paraphrase.split()):
                  continue
  
              scores = []
  
              if len(fields) == 6:
                  # filter equivalence word ( for PPDB v2.0 only.)
                  # entailment = fields[5].strip()
                  # if entailment == 'Equivalence' and self.is_synonym:
                  #     continue
  
                  features = fields[3].strip().split()
                  features = [
                      feature
                      for feature in features
                      for s in self.score_threshold
                      if s in feature
                  ]  # filter by scheme
  
                  for feature in features:
                      scheme, score = feature.split("=")
                      if (
                          scheme in self.score_threshold
                          and float(score)
                          > self.score_threshold[scheme]
                      ):
                          scores.append((scheme, score))
  
                  # # filter by feature/ score
                  # if len(scores) == 0:
                  #     continue
  
              if phrase not in self.dict:
                  self.dict[phrase] = {}
  
              part_of_speeches = [
                  pos
                  for con in constituents
                  for pos in PartOfSpeech.constituent2pos(con)
              ]
  
              for pos in part_of_speeches:
                  if pos not in self.dict[phrase]:
                      self.dict[phrase][pos] = []
  
                  self.dict[phrase][pos].append(
                      {
                          "phrase": phrase,
                          "part_of_speech": pos,
                          "synonym": paraphrase,
                          "scores": scores,
                      }
                  )
  
file_path: nlpaug/nlpaug/model/word_dict/ppdb.py
imports: from nlpaug.util import PartOfSpeech
  from nlpaug.model.word_dict import WordDictionary
label_desc: Use image node_id 4 for calling the Ppdb obj's underlying member method code with example usage: obj.read(model_path) without return types